Commit
•
62a39be
1
Parent(s):
b2868e0
Upload folder using huggingface_hub
Browse files
app.py
ADDED
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import os
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import gradio as gr
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import requests
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from PIL import Image
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from io import BytesIO
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from base64 import b64encode
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SEGMIND_MODEL_URL = "https://api.segmind.com/v1/inpaint-auto"
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def urlToB64(imgUrl):
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return str(b64encode(requests.get(imgUrl).content))[2:-1]
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def imageToB64(img):
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buffered = BytesIO()
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img.save(buffered, format="JPEG")
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return str(b64encode(buffered.getvalue()))[2:-1]
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def generate_image(
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upload_method,
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img_url,
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uploaded_img,
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prompt,
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negative_prompt,
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cn_model,
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cn_processor,
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base_model
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):
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if upload_method == "URL":
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if not img_url:
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raise ValueError("Image URL is required.")
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img_b64 = urlToB64(img_url)
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else:
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if not uploaded_img:
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raise ValueError("Image upload is required.")
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img_b64 = imageToB64(uploaded_img)
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data = {
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"image": img_b64,
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"prompt": prompt,
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"negative_prompt": negative_prompt,
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"samples": 1,
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"base_model": base_model,
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"cn_model": cn_model,
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"cn_processor": cn_processor,
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"scheduler": "DPM++ 2M SDE Karras",
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"num_inference_steps": 25,
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"guidance_scale": 7.5,
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"seed": -1,
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"strength": 0.9,
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"base64": False,
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}
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response = requests.post(
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SEGMIND_MODEL_URL,
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json=data,
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headers={"x-api-key": os.environ['SEGMIND_API_KEY']}
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)
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output_img = Image.open(BytesIO(response.content))
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return output_img
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def invertBox(upload_method):
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# Return gr.update objects with visibility settings
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if upload_method == "URL":
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return gr.update(visible=True), gr.update(visible=False)
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else:
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return gr.update(visible=False), gr.update(visible=True)
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with gr.Blocks() as demo:
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gr.Markdown("### Photo Background Changer")
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gr.Markdown(
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"Change the bavkground of the image in one click to anything that you can imagine"
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)
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with gr.Row():
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upload_method = gr.Radio(
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choices=["URL", "Upload"], label="Choose Image Upload Method", value="URL"
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)
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img_url = gr.Textbox(label="Image URL")
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uploaded_img = gr.Image(type="pil", label="Upload Image", visible=False)
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upload_method.change(
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invertBox, inputs=upload_method, outputs=[img_url, uploaded_img]
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)
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with gr.Row():
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prompt = gr.Textbox(label="Prompt")
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negative_prompt = gr.Textbox(
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label="Negative Prompt",
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value="disfigured, deformed, ugly, floating in air, blur, haze, uneven edges, improper blending, animated, cartoon",
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)
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with gr.Row():
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cn_model = gr.Dropdown(
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label="Select Controlnet Model",
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choices=["Canny", "Depth", "SoftEdge", "OpenPose"],
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value="Depth",
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)
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cn_processor = gr.Dropdown(
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label="Select Controlnet Processor",
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choices=[
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"canny",
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"depth",
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"depth_leres",
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"depth_leres++",
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"hed",
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"hed_safe",
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"mediapipe_face",
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"mlsd",
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"normal_map",
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"openpose",
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"openpose_hand",
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"openpose_face",
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"openpose_faceonly",
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"openpose_full",
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"dw_openpose_full",
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"animal_openpose",
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"clip_vision",
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"revision_clipvision",
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"revision_ignore_prompt",
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"ip-adapter_clip_sd15",
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"ip-adapter_clip_sdxl_plus_vith",
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"ip-adapter_clip_sdxl",
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"color",
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"pidinet",
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"pidinet_safe",
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"pidinet_sketch",
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"pidinet_scribble",
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"scribble_xdog",
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"scribble_hed",
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"segmentation",
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"threshold",
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"depth_zoe",
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"normal_bae",
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"oneformer_coco",
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"oneformer_ade20k",
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"lineart",
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"lineart_coarse",
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"lineart_anime",
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"lineart_standard",
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"shuffle",
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"tile_resample",
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"invert",
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"lineart_anime_denoise",
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"reference_only",
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"reference_adain",
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"reference_adain+attn",
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"inpaint",
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"inpaint_only",
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"inpaint_only+lama",
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"tile_colorfix",
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"tile_colorfix+sharp",
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"recolor_luminance",
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"recolor_intensity",
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"blur_gaussian",
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"anime_face_segment",
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],
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value="canny",
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)
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with gr.Row():
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base_model = gr.Dropdown(
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label="Select Base SD Model to use",
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choices=["Real Vision XL", "SDXL", "Juggernaut XL", "DreamShaper XL"],
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value="Juggernaut XL",
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)
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with gr.Row():
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generate_btn = gr.Button("Generate Image")
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output_image = gr.Image(type="pil")
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+
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generate_btn.click(
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fn=generate_image,
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inputs=[
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upload_method,
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img_url,
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+
uploaded_img,
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172 |
+
prompt,
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173 |
+
negative_prompt,
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174 |
+
cn_model,
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+
cn_processor,
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base_model
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],
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outputs=[output_image],
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)
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+
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demo.launch(debug=True)
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